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Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Bowers A, Saltuklaroglu T, Harkrider A, Cuellar M - PLoS ONE (2013)

Bottom Line: EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri.Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Disorders, University of Arkansas, Fayetteville, Arkansas, United States of America.

ABSTRACT

Background: Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.).

Methods: Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.

Results: ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset.

Conclusions: Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

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Related in: MedlinePlus

Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the left-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
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pone-0072024-g006: Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the left-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.

Mentions: First, to determine whether any significant differences existed between the PasN baseline and the other passive conditions, a 1×3 ANOVA was conducted for the PasN, PasSp+4 dB, and PasTn+4 dB conditions. For the left μ, no significant differences corrected across the entire time-frequency matrix (69×92) were found (pFDR>.05) in 15–20 Hz range, indicating no differences between the PasN baseline condition and the other two passive conditions. Analysis of the active conditions in which discrimination was required (1×4), revealed a significant main effect (pFDR<.05; 69×92) in the 15–19 Hz range for the time period between 600–1200 ms following stimulus offset. To assess which conditions were significantly different from the PasN baseline, a series of paired t-tests were performed. Significant differences (pFDR<.05; 69×92) for the time periods before, during, and after stimulus onset were found for the ActSp+4 dB and ActSp−6 dB only. A paired comparison between the ActSp+4 dB and ActSp−6 dB conditions across the 15–19 Hz range between 600–1200 ms period (pFDR<.05;8×31) revealed a significantly larger peak ERD in the ActSp+4 dB condition just following stimulus offset and lasting until 1100 ms. As such, the left component cluster showed significant effects for only the syllable discrimination task and further showed significant differences in the time period following stimulus offset for correct discrimination trials in the ActSp+4 dB condition relative to the chance trials in the ActSp−6 dB condition (Figure 6).


Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

Bowers A, Saltuklaroglu T, Harkrider A, Cuellar M - PLoS ONE (2013)

Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the left-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3750026&req=5

pone-0072024-g006: Mean ERSPs for correct and chance trials as a function of stimulus type and performance level for the left-hemisphere µ cluster.A) sLORETA solutions depicted on a 3D Van Essen average template; B) mean time-frequency ERSPs (event-related spectral perturbations) as a function of stimulus type (speech and tone) and performance level (correct and chance) for the time-periods prior to stimulus onset, during stimulus presentation, and after stimulus-offset.
Mentions: First, to determine whether any significant differences existed between the PasN baseline and the other passive conditions, a 1×3 ANOVA was conducted for the PasN, PasSp+4 dB, and PasTn+4 dB conditions. For the left μ, no significant differences corrected across the entire time-frequency matrix (69×92) were found (pFDR>.05) in 15–20 Hz range, indicating no differences between the PasN baseline condition and the other two passive conditions. Analysis of the active conditions in which discrimination was required (1×4), revealed a significant main effect (pFDR<.05; 69×92) in the 15–19 Hz range for the time period between 600–1200 ms following stimulus offset. To assess which conditions were significantly different from the PasN baseline, a series of paired t-tests were performed. Significant differences (pFDR<.05; 69×92) for the time periods before, during, and after stimulus onset were found for the ActSp+4 dB and ActSp−6 dB only. A paired comparison between the ActSp+4 dB and ActSp−6 dB conditions across the 15–19 Hz range between 600–1200 ms period (pFDR<.05;8×31) revealed a significantly larger peak ERD in the ActSp+4 dB condition just following stimulus offset and lasting until 1100 ms. As such, the left component cluster showed significant effects for only the syllable discrimination task and further showed significant differences in the time period following stimulus offset for correct discrimination trials in the ActSp+4 dB condition relative to the chance trials in the ActSp−6 dB condition (Figure 6).

Bottom Line: EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri.Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

View Article: PubMed Central - PubMed

Affiliation: Department of Communication Disorders, University of Arkansas, Fayetteville, Arkansas, United States of America.

ABSTRACT

Background: Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.).

Methods: Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB.

Results: ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset.

Conclusions: Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

Show MeSH
Related in: MedlinePlus